← Early-stage Startup Interview Insights
The 'any language' part sounds freeing until you realize it means you have to justify your choice too.
Start by clarifying requirements such as signal characteristics, cutoff frequency, and performance constraints. Then choose an appropriate filter design (e.g., FIR or IIR) and implement it with optimizations like circular buffers, SIMD, or fixed-point arithmetic. Finally, discuss trade-offs between accuracy, latency, and computational cost.
Pro tip: In an early-stage startup, emphasize simplicity and maintainability: a well-optimized simple filter often beats a complex one that's hard to tune. Also, mention how you'd validate performance with real data and iterate.
Ask about signal type, sampling rate, cutoff frequency, attenuation, phase linearity, and real-time constraints. This ensures you design the right filter for the context.
Select between FIR (linear phase, stable) and IIR (computationally efficient, non-linear phase). Consider windowed-sinc, Butterworth, or Chebyshev based on trade-offs.
Use circular buffers for FIR, direct form II for IIR, and leverage SIMD, loop unrolling, or fixed-point arithmetic. Precompute coefficients and avoid dynamic memory allocation in the hot path.
Measure computational complexity (O(N) per sample), memory usage, and latency. Profile with realistic data and consider hardware acceleration if needed.
Explain how choices affect accuracy, latency, and resource usage. For a startup, prioritize simplicity and adaptability over extreme optimization.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.